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From bench to bedside: Single-cell analysis for cancer immunotherapy

期刊

CANCER CELL
卷 39, 期 8, 页码 1062-1080

出版社

CELL PRESS
DOI: 10.1016/j.ccell.2021.07.004

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资金

  1. Lustgarten Foundation Pancreatic Cancer Research grant
  2. Sol Goldman Pancreatic Cancer Research Center grant
  3. Emerson Collective Cancer Research Fund
  4. Allegheny Health Network (AHN) grant [U01CA212007, U01CA253403]
  5. JHU [P30CA006973, F31CA250135-01A1]
  6. Kavli NDI postdoctoral fellowship

向作者/读者索取更多资源

Single-cell technologies are powerful tools for cancer research, providing insights into tumor heterogeneity and cell state transitions affecting therapeutic response. Analyzing clinical samples is promising for precision medicine but requires coordination among multi-disciplinary teams for data accuracy and interpretation.
Single-cell technologies are emerging as powerful tools for cancer research. These technologies characterize the molecular state of each cell within a tumor, enabling new exploration of tumor heterogeneity, microenvironment cell-type composition, and cell state transitions that affect therapeutic response, particularly in the context of immunotherapy. Analyzing clinical samples has great promise for precision medicine but is technically challenging. Successfully identifying predictors of response requires well-coordinated, multi-disciplinary teams to ensure adequate sample processing for high-quality data generation and computational analysis for data interpretation. Here, we review current approaches to sample processing and computational analysis regarding their application to translational cancer immunotherapy research.

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